The economic wedge
Memory lowers token waste. Hosted open-weight inference lowers the price per token. The savings stack.

Investor One-Pager
We make enterprise AI cheaper and more useful by giving it governed memory and a lower-cost inference path.
RecordorAI gives enterprise AI systems a memory layer that retrieves the right context when it matters. The customer gets better answers, fewer wasted tokens, auditability, and a predictable enterprise bill.
Memory lowers token waste. Hosted open-weight inference lowers the price per token. The savings stack.
Customer memory is not stored in our cloud. Hosted inference receives only policy-filtered context, or runs on-prem for strict buyers.
Start with SaaS and AI-native platforms, then expand into regulated accounts where control and predictable spend matter more.
This version proves the business without trying to build the entire $22M plan at once. It funds a three-year plan for product, enterprise pilots, compliance, a small sales team, and starter infrastructure.
The round is not meant to buy scale forever. It is meant to prove that the enterprise wedge repeats.
Launch the inference beta, convert 3 SaaS pilots, start SOC 2, and keep hardware spend tight.
Turn pilots into production, add 15 SaaS customers and 2 regulated customers, complete SOC 2 Type II.
Reach 50 SaaS customers, 6 regulated customers, 8 platform customers, and 25 inference subscriptions.
The clean base case is $24M ARR by Year 3. The underwrite can live at 8-12x ARR, with premium upside if RecordorAI becomes strategic AI infrastructure.